The present invention is directed generally to a new system, software and method that enable the examination of a database, particularly, a financial database such as, for example, a general ledger, to identify records (transactions) that are anomalous or otherwise significant (e.g., as an indicator of fraudulent activity). More particularly, the system, software and method according to the present invention employ real-time “n-” or multi-dimensional data interrogation analytics, particularly, online analytical processing (“OLAP”), to enable real-time data interrogation in a forensic accounting application.
As is known to those of ordinary skill in the art, OLAP is a category of software tools that provides analysis of data stored in a database. OLAP tools enable users to analyze different dimensions of multi-dimensional data. OLAP provides distinct advantages over known data mining tools (a class of database applications that look for hidden patterns in a group of data)—including the capability to identify more than just mere relationships among data, but rather the capacity to identify aspects of the data that are anomalous. As described in greater detail hereinafter, the present invention (including through its use of statistical functions) provides a new forensic tool that leverages the advantages of OLAP.
There is an ongoing effort in the accounting/auditing field, particularly, in the forensic accounting field, to design procedures to test the appropriateness of records in large financial databases. The system, software and method according to the present invention are a new response to the needs of this effort.
Forensic accounting involves the integration of accounting, statistics, technology and investigative skills. Forensic accountants are typically retained to investigate, analyze and interpret financial evidence (e.g., in investigations of criminal matters such as employee theft, securities and insurance fraud), to assist in the analysis and presentation of financial evidence, and to communicate their findings (e.g., by testifying in court as expert witnesses and preparing visual aids to support trial evidence). Forensic accountants are also called upon to assist auditors in investigating potential fraudulent activity. Forensic accountants can be engaged in public practice or by insurance companies, banks, police forces, government agencies and other organizations.
Conventionally, forensic examiners use commercial database software such as, for example, ACL, MS Access and MS SQL Server, to review general ledger transaction entries. However, these commercial tools do not perform OLAP and require the user to program a query for each question posed or test with respect to the data. Moreover, these commercial tools report voluminous amounts of data that are unwieldy and unreasonable to review and are often not useful.
Accordingly, it is desired to provide a new system, software and method for use in forensic accounting investigations of financial databases that overcome the disadvantages associated with conventional software and methods and that enable, using OLAP, (i) an analysis of the same data sets, while breaking the data sets into different populations (e.g., income statement populations such as, for example, sales, cost of sales, labor, taxes, depreciation/amortization, interest and other income/expense), (ii) the identification of relationships between the populations and between the inquiries or tests with respect to the data, and (iii) the generation of results that are specific (useful) and that can translate into recommendations for the relevant users.